GSK3β and mTORC1 Represent 2 Distinct Signaling Markers in Peripheral Blood Mononuclear Cells of Drug-Naive, First Episode of Psychosis Patients

Abstract Background and Hypothesis Schizophrenia is characterized by a complex interplay between genetic and environmental risk factors converging on prominent signaling pathways that orchestrate brain development. The Akt/GSK3β/mTORC1 pathway has long been recognized as a point of convergence and etiological mechanism, but despite evidence suggesting its hypofunction, it is still not clear if this is already established during the first episode of psychosis (FEP). Study Design Here, we performed a systematic phosphorylation analysis of Akt, GSK3β, and S6, a mTORC1 downstream target, in fresh peripheral blood mononuclear cells from drug-naive FEP patients and control subjects. Study Results Our results suggest 2 distinct signaling endophenotypes in FEP patients. GSK3β hypofunction exhibits a promiscuous association with psychopathology, and it is normalized after treatment, whereas mTORC1 hypofunction represents a stable state. Conclusions Our study provides novel insight on the peripheral hypofunction of the Akt/GSK3β/mTORC1 pathway and highlights mTORC1 activity as a prominent integrator of altered peripheral immune and metabolic states in FEP patients.


Supplementary Tables
Supplementary Table 1 Spearman's correlation coefficients (r) and P values (in parentheses) are indicated. Note that this corresponds to reanalysis of the subgroup of 32 patients from Figure 2C that were available for follow-up and it highlights weak correlations of pGSK3β baseline levels with PANSS-G and PANSS-T scores (in bold). No significant differences were found for pAkt and pS6 correlations compared to data in Figure 2C.   blotting with different antibodies. Note that in some cases (e.g., S6/pS6, control-FEP), lower parts of two gels with different groups of samples were blotted on the same membrane. In other cases (e.g., Akt/p-Akt, control-FEP and other images), membrane strips with different groups of samples were imaged simultaneously. In the before-after group, whole membranes or cut strips were first probed for a signaling marker and subsequently for GAPDH or tubulin. For technical details on design and methodology please refer to Supplementary Methods.

PBMCs isolation and protein extraction
Briefly, diluted whole blood was gently layered on the top of Ficoll Histopaque (4ml) in a 15ml centrifuge tube and was centrifuged at 1800rpm for 10min (20 o C). The cell layer containing PBMCs at the interface between plasma and Ficoll was transferred to a clean tube and was washed with sterile PBS, with sequential centrifugation steps at 1600 rpm and then at 1400 rpm for 10 min each (20 o C). The washed PBMC pellet was snap-frozen in liquid nitrogen and stored at -80 o C. Stored PBMC pellets were thawed on ice and lysed with lysis buffer (20mM Bicine, pH=7,6, 0,6% w/v CHAPS) supplemented with phosphatase inhibitors (2mM sodium fluoride, 2mM sodium orthovanadate, 2mM beta-glycero phosphate, 2mM sodium molybdate), 0.2mM PMSF and 0,4% Protease Inhibitor cocktail 3 (539134, Calbiochem). After solubilization of proteins and centrifugation at 15000 rpm for 20min (4 o C) to remove particulate material, the cleared supernatants were aliquoted and stored at -80 o C. Protein concentration was determined by the BCA Assay Kit (Pierce II, USA).

Experimental Design of Western Blot Analysis and quantification
Samples were run on 10% SDS-polyacrylamide gels and transferred to nitrocellulose membrane at with external standard samples. We expressed each normalized phospho-specific signal as a ratio against total expression of GAPDH (for pAkt and pGSK3β) and S6 (for pS6), which were measured on the same gel (for pAkt/GAPDH and pGSK3β/GAPDH pairs) or in sister gels (for pS6/S6 pairs) and normalized accordingly to external standards. We also included measurements for α-tubulin on the pS6 and S6 gels in this dataset (figure 3). Membranes were routinely probed for pAkt or pGSK3 and subsequently for GAPDH, or S6 or pS6 and subsequently for α-tubulin (representative uncropped images are shown in Supplementary figure 1). The final dataset was not z-score transformed for the analysis in figure 3 and Supplementary Tables 3 and 4.

Multivariate exploratory analysis of phosphorylation values
The final dataset of pAkt, pGSK3β and pS6 phosphorylation values for 36 control and 36 FEP patient samples patients was imported into R (R version 4.1.0) using Rstudio (Version 1.4.1717) as continuous variables. After confirming, through frequency histograms and Shapiro-Wilk normality tests (p-value for all variables was <0.05), that none of the three variables follow a normal distribution, the variables were standardized as Z-scores and were used for all subsequent analyses.
Differences in phosphorylation levels of the three kinases between cases and controls were summarised into boxplots for each kinase, and non-parametric Mann-Whitney U tests were performed to infer statistical significances. Scatterplot matrices were plotted to investigate correlations. For each pair, a Spearman's test of association was applied to calculate the correlation estimate, while association p-values were calculated via the asymptotic approximation. Plots were generated using ggplot R package. Code, figures and detailed information on the analysis can be found on GitHub (https://github.com/digrigor/Schizo-FEP-Akt_paper_2021).

Regression analysis
A logistic regression using the logit distribution was calculated to assess the effects of pAkt, pGSK3 and pS6 phosphorylation values (continuous independent predictors) to the sample state (control vs FEP; binary dependent variable). The data was modelled using the "binomial" family of R's glm() function (phenotype ~ pAkt_zscore + pGSK3_zscore + pS6_zscore To investigate whether the interaction between the three continuous predictors also have an effect we fit a logistic regression model including the same pAkt, pGSK3 and pS6 variables as well as all the interactions between them using the "binomial" family of R's glm() function (phenotype ~ pAkt_zscore * pGSK3_zscore * pS6_zscore). The analysis revealed that the interaction between the variables do not have any effect (Supplementary Table 2).

Assessment of reproducibility in western blot analyses
Reproducibility was assessed by running the same samples of external standard and preselected control subjects in different gels and in different rounds. For the external standard, the calculated relative coefficient of variation was 7.5% for pAkt (n=10 from 5 different gels) and 7.8 % for pGSK3 (n=16 from 8 different gels) from a representative round. Accuracy of the densitometric analyses was assessed by performing dual measurements of ECL signals by two different researchers. The calculated relative coefficient of variation was 8% for the baseline vs after treatment pAkt and pGSK3 datasets. External standard sample was validated by running different amounts of protein (2, 5 and 10μg) on the same gel and calculating the final normalized pAkt. pGSK3β and pS6 values. The amount of protein did not substantially change the final values which were pAkt = 0.74±0.06 (n=6), pGSK3β =1.65±0.17 (n=6), and pS6=0.71±0.09 (n=6) for a representative experiment.